Published Paper Details:

Artificial Intelligence (AI) has emerged as a transformative force in manufacturing, enhancing efficiency, reducing costs, and improving quality control. The paint industry, characterized by complex production processes, is increasingly leveraging AI-driven solutions such as predictive maintenance, process automation, and real-time quality monitoring. This study examines the impact of AI implementation in paint manufacturing, focusing on three key areas: operational efficiency, cost reduction, and quality control. Using a mixed-method approach, including industry surveys and case studies, the research evaluates AI adoption levels, its tangible benefits, and the perception of industry professionals. Findings indicate that AI significantly enhances operational efficiency by optimizing workflows and reducing downtime. Cost savings are primarily observed through waste minimization and energy efficiency, while AI-driven quality control mechanisms improve product consistency. However, challenges such as high implementation costs and workforce adaptation persist. The study concludes with recommendations for scalable AI adoption in the paint manufacturing sector.